Prerequisites
- A strong foundational understanding of artificial intelligence and cloud computing principles.
- Basic knowledge of programming languages, data structures, and algorithms.
- Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Basic understanding of mathematics for machine learning, essential for AI model building.
Course outline
- 1
Lesson 1: Fundamentals of Artificial Intelligence (AI) and Cloud
- 1.1 Introduction to AI and Its Application
- 1.2 Overview of Cloud Computing and Its Benefits
- 1.3 Benefits and Challenges of AI-Cloud Integration
- 2
Lesson 2: Introduction to Artificial Intelligence
- 2.1 Basic Concepts and Principles of AI
- 2.2 Machine Learning and Its Applications
- 2.3 Overview of Common AI Algorithms
- 2.4 Introduction to Python Programming for AI
- 3
Lesson 3: Fundamentals of Cloud Computing
- 3.1 Cloud Service Models
- 3.2 Cloud Deployment Models
- 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)
- 4
Lesson 4: AI Services in the Cloud
- 4.1 Integration of AI Services in Cloud Platform
- 4.2 Working with Pre-built Machine Learning Models
- 4.3 Introduction to Cloud-based AI tools
- 5
Lesson 5: AI Model Development in the Cloud
- 5.1 Building and Training Machine Learning Models
- 5.2 Model Optimization and Evaluation
- 5.3 Collaborative AI Development in a Cloud Environment
- 6
Lesson 6: Cloud Infrastructure for AI
- 6.1 Setting Up and Configuring Cloud Resources
- 6.2 Scalability and Performance Considerations
- 6.3 Data Storage and Management in the Cloud
- 7
Lesson 7: Deployment and Integration
- 7.1 Strategies for Deploying AI Models in the Cloud
- 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
- 7.3 API Usage and Considerations
- 8
Lesson 8: Future Trends in AI+ Cloud Integration
- 8.1 Introduction to Future Trends
- 8.2 AI Trends Impacting Cloud Integration
- 9
Lesson 9: Capstone Project
- 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem
- 10
Optional Lesson: AI Agents for Cloud Computing
- Understanding AI Agents
- Case Studies
- Hands-On Practice with AI Agents
Materials
All necessary course materials are included.
System requirements
Minimum technical expectations for the online learning environment. Your IT team can use this as a checklist.
Internet connectivity
Cable, Fiber, DSL, or LEO Satellite (i.e. Starlink) internet with speeds of at least 10mb/sec download and 5mb/sec upload are recommended for the best experience.
While cellular hotspots may allow access to our courses, users may experience connectivity issues by trying to access our learning management system. This is due to the potential high download and upload latency of cellular connections. Therefore, it is not recommended that students use a cellular hotspot as their primary way of accessing their courses.
Hardware
CPU: 1 GHz or higher RAM: 4 GB or higherResolution: 1280 x 720 or higher. 1920x1080 resolution is recommended for the best experience. Speakers / Headphones. Microphone for Webinar or Live Online sessions.
Operating system
Windows 7 or higher. Mac OSX 10 or higher. Latest Chrome OS. Latest Linux Distributions.
While we understand that our courses can be viewed on Android and iPhone devices, we do not recommend the use of these devices for our courses. The size of these devices do not provide a good learning environment for students taking online or live online based courses.
Web browser
Latest Google Chrome is recommended for the best experience. Latest Mozilla FireFox. Latest Microsoft Edge. Latest Apple Safari
Recommended software
Office suite software (Microsoft Office, OpenOffice, or LibreOffice). PDF reader program (Adobe Reader, FoxIt). Courses may require other software that is described in the above course outline.
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